{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "79ede424",
   "metadata": {},
   "source": [
    "This notebook discusses `lmfit.ModelResult.eval_uncertainty()` and results from it.  It was sparked by a discussion at https://groups.google.com/g/lmfit-py/c/U0_zD3F9jw8/m/75P6TccSAQAJ  (Dec, 2023).\n",
    "\n",
    "\n",
    "The code here uses the `eval_uncertainty_dscale` branch, which adds the optional scaling parameter `dscale` used to set the step size for derivatives calculated in `lmfit.Model.eval_uncertainty()`.\n",
    "\n",
    "The `NIST_Gauss2.data` data file used here are from the `examples` folder in the lmfit source tree.  The values for the original question are included in the code. \n",
    "\n",
    "We'll start with a modified version of the original question."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c1a8a826",
   "metadata": {},
   "outputs": [],
   "source": [
    "# some basic imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from lmfit import Model, models\n",
    "from uncertainties import umath\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "abc3d93d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[Model]]\n",
      "    Model(expfunc)\n",
      "[[Fit Statistics]]\n",
      "    # fitting method   = leastsq\n",
      "    # function evals   = 33\n",
      "    # data points      = 25\n",
      "    # variables        = 3\n",
      "    chi-square         = 2.0705e-08\n",
      "    reduced chi-square = 9.4115e-10\n",
      "    Akaike info crit   = -516.793759\n",
      "    Bayesian info crit = -513.137132\n",
      "    R-squared          = 0.82814534\n",
      "[[Variables]]\n",
      "    offset:     6.9536e-05 +/- 1.6571e-05 (23.83%) (init = 0.0001)\n",
      "    amplitude: -675692.422 +/- 5434521.95 (804.29%) (init = -9000)\n",
      "    decay:     -22.2179797 +/- 8.14731073 (36.67%) (init = -20)\n",
      "[[Correlations]] (unreported correlations are < 0.100)\n",
      "    C(amplitude, decay)  = +0.9999\n",
      "    C(offset, decay)     = +0.8711\n",
      "    C(offset, amplitude) = +0.8671\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ries et al - hard clam data\n",
    "# TA:DIC        Calc rate [mmol/g/hr] (compiled)\n",
    "x = [1.147058824, 1.147058824, 1.147058824, 1.147058824, 1.147058824,\n",
    "     1.147058824, 1.147058824, 1.105700713, 1.105700713, 1.105700713,\n",
    "     1.105700713, 1.105700713, 1.061177816, 1.061177816, 1.061177816,\n",
    "     1.061177816, 1.061177816, 1.061177816, 1.061177816, 0.996137132,\n",
    "     0.996137132, 0.996137132, 0.996137132, 0.996137132, 0.996137132]\n",
    "\n",
    "y = [0.00010823592100442932, 3.3303360309055184e-05, 0.00013321344123622074,\n",
    "     6.660672061811037e-05, 4.162920038631898e-05, 5.411796050221466e-05,\n",
    "     2.497752023179139e-05, 5.8280880540846574e-05, 4.995504046358278e-05,\n",
    "     3.746628034768708e-05, 7.493256069537416e-05, 2.9140440270423287e-05,\n",
    "     5.8280880540846574e-05, -1.6651680154527592e-05, 2.9140440270423287e-05,\n",
    "     6.244380057947847e-05, 4.995504046358278e-05, 3.746628034768708e-05,\n",
    "     4.162920038631898e-06, -9.574716088853365e-05, -0.00013737636127485265,\n",
    "     -0.00012488760115895694, -6.660672061811037e-05, -7.909548073400604e-05,\n",
    "     -7.076964065674227e-05]\n",
    "\n",
    "def expfunc(x, offset, amplitude, decay):\n",
    "    return offset + amplitude * np.exp(decay * x)\n",
    "\n",
    "mod = Model(expfunc)\n",
    "pars = mod.make_params(offset=1.e-4, amplitude=-9000, decay=-20)\n",
    "result = mod.fit(y, pars, x=x)\n",
    "\n",
    "print(result.fit_report())\n",
    "\n",
    "plt.plot(x, y, '+', label='observations')\n",
    "plt.plot(x, result.best_fit, '-', label='fit')\n",
    "\n",
    "xpred = np.linspace(.95, 1.3, 100)\n",
    "ypred = result.eval(x=xpred)\n",
    "\n",
    "plt.plot(xpred, ypred, '--', label='projected')\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bacb89cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17ba36150>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# now if we plot the predicted uncertainty\n",
    "\n",
    "plt.plot(x, y, '+', label='observations')\n",
    "plt.plot(xpred, ypred, '--', label='projected')\n",
    "\n",
    "dypred = result.eval_uncertainty(x=xpred, sigma=2, dscale=0.333)\n",
    "\n",
    "plt.fill_between(xpred, ypred-dypred, ypred+dypred,\n",
    "                 color=\"#DD9DAB22\", label=r'2-$\\sigma$ uncertainty band')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25e91a4d",
   "metadata": {},
   "source": [
    "and the uncertainty looks enormous.   The basic quesstion is: Why?  The user showed results from Matlab that were much smaller. Why the difference?\n",
    "\n",
    "In the lmfit 1.2.2, the value for `dscale` is fixed in the code to 0.33333.  \n",
    "If we lower that, the result can change dramatically:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f7fe9bfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17bcaba10>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, '+', label='observations')\n",
    "plt.plot(xpred, ypred, '--', label='projected')\n",
    "\n",
    "dypred_001 = result.eval_uncertainty(x=xpred, sigma=2, dscale=0.001)\n",
    "plt.fill_between(xpred, ypred-dypred, ypred+dypred,\n",
    "                 color=\"#DD9DAB22\", label=r'2-$\\sigma$ band, dscale=0.333')\n",
    "plt.fill_between(xpred, ypred-dypred_001, ypred+dypred_001,\n",
    "                 color=\"#88AABB88\", label=r'2-$\\sigma$ band, dscale=0.001')\n",
    "plt.ylim((-0.001, 0.001))\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73e68951",
   "metadata": {},
   "source": [
    "The uncertainties using dscale=0.001 appear to be much closer to the ones from Matlab.  This then is argued as being \"correct\".  \n",
    "\n",
    "I have a concern with this though.  In that plot above, the gray band is meant to represent the 95% confidence level for the model / fit.  Not that below x=1.00, it never goes above 0: that is saying that one can be 95% confident that the value of model for x<1 is negative.\n",
    "\n",
    "But the best fit value for the offset is definitely positive: \n",
    "    offset = 6.95e-05 +/- 1.67e-05  \n",
    "\n",
    "The best fit value for the amplitude of the exponential is negative, but its 1-sigma uncertainty is 50x its best-fit value:  \n",
    "    amplitude: -0.676e6 +/- 5.4e6 \n",
    "    \n",
    "That value is definitely consistent with 0.0.  It is barely negative.  The 2-sigma uncertainty for this term would be -1 +/- 100.   \n",
    "\n",
    "How can then 95% confidence level for x<1 only include negative values? \n",
    "\n",
    "\n",
    "As a more-or-less independent check of confidence levels with Python, we can use the uncertainties package to propagate uncertainties from the correlated parameters, using its `umath` module which we imported above, and the `result.uvars` values, which are the `ufloats` (values with uncertainties that can be propagated) from the `uncertainties` package.   Note, however, that unlike `ModelResult.eval_uncertainty`, this takes into account only the reported uncertainties and correlations between fitted parameters.  It does not take into account the degrees of freedom in the fit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "33497e9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "uvars = result.uvars\n",
    "dy_umath = []\n",
    "for _x in xpred:\n",
    "    dy_umath.append((uvars['offset'] + uvars['amplitude'] * umath.exp(uvars['decay']*_x)).s)\n",
    "\n",
    "# now we convert to an array and double it to get the 2-sigma confidence level\n",
    "dy_umath = 2*np.array(dy_umath)\n",
    "\n",
    "plt.plot(xpred, dypred_001, '-', label='from lmfit, dscale=0.001')\n",
    "plt.plot(xpred, dy_umath, '--', label='from uncertainties')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27cc92f4",
   "metadata": {},
   "source": [
    "OK, those are very close, and appear to be very close to what Matlab gives. Again, apparently correct.. maybe.\n",
    "\n",
    "\n",
    "But first, is using the default `dscale=0.333` always too big?  It turns out that it is not.  \n",
    "Let's test that with a different dataset - the NIST Gauss2 dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eeabba69",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[Model]]\n",
      "    ((Model(gaussian, prefix='g1_') + Model(gaussian, prefix='g2_')) + Model(exponential, prefix='bkg_'))\n",
      "[[Fit Statistics]]\n",
      "    # fitting method   = leastsq\n",
      "    # function evals   = 55\n",
      "    # data points      = 250\n",
      "    # variables        = 8\n",
      "    chi-square         = 1247.52821\n",
      "    reduced chi-square = 5.15507524\n",
      "    Akaike info crit   = 417.864631\n",
      "    Bayesian info crit = 446.036318\n",
      "    R-squared          = 0.99648654\n",
      "[[Variables]]\n",
      "    g1_amplitude:   4257.77399 +/- 42.3838008 (1.00%) (init = 3000)\n",
      "    g1_center:      107.030957 +/- 0.15006868 (0.14%) (init = 100)\n",
      "    g1_sigma:       16.6725789 +/- 0.16048222 (0.96%) (init = 10)\n",
      "    g2_amplitude:   2493.41715 +/- 36.1696228 (1.45%) (init = 3000)\n",
      "    g2_center:      153.270104 +/- 0.19466723 (0.13%) (init = 150)\n",
      "    g2_sigma:       13.8069453 +/- 0.18680099 (1.35%) (init = 10)\n",
      "    bkg_amplitude:  99.0183280 +/- 0.53748639 (0.54%) (init = 100)\n",
      "    bkg_decay:      90.9508824 +/- 1.10310769 (1.21%) (init = 80)\n",
      "    g1_fwhm:        39.2609222 +/- 0.37790675 (0.96%) == '2.3548200*g1_sigma'\n",
      "    g1_height:      101.880228 +/- 0.59217122 (0.58%) == '0.3989423*g1_amplitude/max(1e-15, g1_sigma)'\n",
      "    g2_fwhm:        32.5128710 +/- 0.43988270 (1.35%) == '2.3548200*g2_sigma'\n",
      "    g2_height:      72.0455936 +/- 0.61721901 (0.86%) == '0.3989423*g2_amplitude/max(1e-15, g2_sigma)'\n",
      "[[Correlations]] (unreported correlations are < 0.500)\n",
      "    C(g1_amplitude, g1_sigma)   = +0.8243\n",
      "    C(g2_amplitude, g2_sigma)   = +0.8154\n",
      "    C(bkg_amplitude, bkg_decay) = -0.6946\n",
      "    C(g1_sigma, g2_center)      = +0.6842\n",
      "    C(g1_center, g2_amplitude)  = -0.6689\n",
      "    C(g1_center, g2_sigma)      = -0.6520\n",
      "    C(g1_amplitude, g2_center)  = +0.6477\n",
      "    C(g1_center, g2_center)     = +0.6205\n",
      "    C(g1_center, g1_sigma)      = +0.5075\n",
      "    C(g1_amplitude, bkg_decay)  = -0.5074\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17bd3e050>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# load and set up fit for the NIST Gauss2 data\n",
    "dat = np.loadtxt('NIST_Gauss2.dat')\n",
    "xg = dat[:, 1]\n",
    "yg = dat[:, 0]\n",
    "\n",
    "nmodel = (models.GaussianModel(prefix='g1_') +\n",
    "          models.GaussianModel(prefix='g2_') +\n",
    "          models.ExponentialModel(prefix='bkg_'))\n",
    "\n",
    "params = nmodel.make_params(bkg_amplitude=100, bkg_decay=80,\n",
    "                            g1_amplitude=3000,\n",
    "                            g1_center=100,\n",
    "                            g1_sigma=10,\n",
    "                            g2_amplitude=3000,\n",
    "                            g2_center=150,\n",
    "                            g2_sigma=10)\n",
    "\n",
    "result = nmodel.fit(yg, params, x=xg)\n",
    "print(result.fit_report(min_correl=0.5))\n",
    "\n",
    "plt.plot(xg, yg, 'o', label='data')\n",
    "plt.plot(xg, result.init_fit,  label='initial fit')\n",
    "plt.plot(xg, result.best_fit, label='best-fit')\n",
    "\n",
    "\n",
    "yg_dy333 = result.eval_uncertainty(sigma=2, dscale=0.333)\n",
    "yg_dy001 = result.eval_uncertainty(sigma=2, dscale=0.001)\n",
    "\n",
    "plt.fill_between(xg, result.best_fit-yg_dy001, result.best_fit-yg_dy001,\n",
    "                 color=\"#8888BB44\", label=r'2-$\\sigma$ band, dscale=0.001')\n",
    "                 \n",
    "plt.fill_between(xg, result.best_fit-yg_dy333, result.best_fit-yg_dy333,\n",
    "                 color=\"#BB88BB88\", label=r'2-$\\sigma$ band, dscale=0.333')\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "354963be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17ba03a10>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# those uncertainty bands are too small and too close to tell apart, so let's plot just them:\n",
    "\n",
    "plt.plot(xg, yg_dy001,  label=r'2-$\\sigma$ band, dscale=0.001')\n",
    "plt.plot(xg, yg_dy333,  label=r'2-$\\sigma$ band, dscale=0.333')\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "497b877b",
   "metadata": {},
   "source": [
    "those uncertainties are right on top of each other.  So `dscale=0.333` is not always wrong!\n",
    "\n",
    "OK, well, maybe that's an easier case. Let's try a different exponential decaying data set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "644e80fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[Model]]\n",
      "    Model(expfunc)\n",
      "[[Fit Statistics]]\n",
      "    # fitting method   = leastsq\n",
      "    # function evals   = 38\n",
      "    # data points      = 21\n",
      "    # variables        = 3\n",
      "    chi-square         = 3.6944e-04\n",
      "    reduced chi-square = 2.0524e-05\n",
      "    Akaike info crit   = -223.909014\n",
      "    Bayesian info crit = -220.775447\n",
      "    R-squared          = 0.99982908\n",
      "[[Variables]]\n",
      "    offset:    -0.49805969 +/- 0.00344877 (0.69%) (init = -0.1)\n",
      "    amplitude:  2.86110664 +/- 0.02355887 (0.82%) (init = 0.2)\n",
      "    decay:     -0.30064521 +/- 0.00281076 (0.93%) (init = -0.1)\n",
      "[[Correlations]] (unreported correlations are < 0.100)\n",
      "    C(amplitude, decay)  = -0.9273\n",
      "    C(offset, decay)     = -0.8961\n",
      "    C(offset, amplitude) = +0.7041\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17bd0b8d0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iYli8eDEul4t//OMfjB49mm+++YaYmBjee+89pk+fzt///neGDx/OW2+9xcyZM+natevp/vM2mMJLE4sIiqBPbB+2HtvKusx1TOw20eqSRERalGJ3Mef+61xL3nvt9WsJc4Y1uH1SUhJ//etfMQyDHj16sHXrVv761796w8uoUaO4//77ve0nTZrE9ddfz9SpUwHo3r07M2fOZOTIkbz88sukp6fzySefkJKSwrnnVv4bzJo1i169etVZw7/+9S+OHj3K+vXriYmJAeCMM87wvh4eHo7D4SAh4Yc/tpcvX87WrVvJysrydj8999xzfPDBB7z//vvcfvvtPP/889x8883ceuutADz99NMsW7asWa6+qNvIB4YkDAFgbcZaiysRERErDR06tNqVmmHDhrFnzx4qKioAGDx4cLX2GzduZPbs2YSHh3uXSy+9FI/HQ1paGjt37sThcFTbrmfPnkRFRdVZw+bNmxkwYIA3uDTExo0bKSgoIDY2tlotaWlp7N27F4CdO3cybNiwatv9+Gdf0ZUXHzg38VxmbZvFusx1mKbZqEuMIiJSv1BHKGuvt+aPw1BHaJPur02bNtV+9ng8/OY3v2HKlCk12nbq1Indu3cDNOpzJTS08TV7PB4SExNZuXJljdfqC0rNReHFB86OOxunzUlmYSbp+el0juxsdUkiIi2GYRiN6rqxUkpKSo2fu3fvjt1ur7X9wIED2b59e7VunZP16tULt9vNhg0bGDKk8ir/7t27OXHiRJ01nHXWWfzzn/8kJyen1qsvQUFB3itBJ9eRmZmJw+GgS5cuddaSkpLCpEmTqh1fc1C3kQ+EOkLp364/oK4jEZHW7ODBg0ybNo3du3fzzjvv8MILL3DvvffW2f6BBx5gzZo13HXXXWzevJk9e/awcOFC7rnnHgB69OjB2LFjue2221i7di0bN27k1ltvrffqyi9/+UsSEhK48sor+e9//8u+ffuYN28ea9asASrvekpLS2Pz5s0cO3aM0tJSLr74YoYNG8aVV17Jp59+yv79+/nqq6949NFH2bCh8hE49957L6+//jqvv/4633zzDdOnT2f79u1N+K9XN4UXHxmSWJmIdcu0iEjrNWnSJIqLixkyZAh33XUX99xzD7fffnud7c866yxWrVrFnj17GD58OAMGDOCxxx4jMTHR2+aNN94gKSmJkSNHctVVV3lvZ65LUFAQn332GXFxcYwfP55+/frxzDPPeK/+XH311YwdO5aLLrqIdu3a8c4772AYBosXL2bEiBHcfPPNnHnmmVx33XXs37+f+Ph4AK699lr+8Ic/8MADDzBo0CAOHDjAnXfe2UT/cvUzzKobzluIvLw8XC4Xubm5REZGWlbHpiObmLxkMjEhMay4ZgU2QzlRRKSxSkpKSEtLIzk5mZCQEKvLaZQLL7yQs88+u9q0/VL3OW3M57c+UX2kX9t+hDpCySnJ4dsT31pdjoiISIuh8OIjTrvT+6BGjXsRERFpOgovPqTnHImItF4rV65Ul5GPKLz4UNWg3Q1HNuD2uC2uRkREpGVQePGhntE9iQyKpKC8gJ3ZO60uR0REpEVQePEhu83OOQnnALA2U+NeREROVwu7MbZVa4pzqfDiY+cmVo57WXN4jcWViIgEHqfTCUBRUZHFlUhTqTqXVef2dOjxAD52XvvzANiUtYmi8qKAmdJaRMQf2O12oqKiyMrKAiAsLEzPiwtQpmlSVFREVlYWUVFRdT4ioSEUXnysU0QnOoR34FDBITYc2cCIjiOsLklEJKAkJCQAeAOMBLaoqCjvOT1dCi8+ZhgG57U/j/988x++OvyVwouISCMZhkFiYiJxcXGUl5dbXY78BE6n8yddcami8NIMTg4vIiJyeux2e5N88Eng04DdZjAkcQh2w05abhoZBRlWlyMiIhLQFF6aQWRQJP3a9gPQ1RcREZGfSOGlmVTddaTwIiIi8tMovDSTYe2HAZCSkUKFp8LiakRERAKXwksz6du2LxHOCPLK8tievd3qckRERAKWwkszcdgcDG0/FFDXkYiIyE+h8NKMqrqO9KgAERGR06fw0oyqBu1uObqF/LJ8i6sREREJTAovzahDeAe6RHahwqxgXeY6q8sREREJSAovzUxdRyIiIj+Nwksz03wvIiIiP43CSzMbkjAEh83BwfyDHMg7YHU5IiIiAUfhpZmFOcMYFDcIgC+++8LiakRERAKPwosFhnccDsDq71ZbXImIiEjgUXixQFV42XBkA0XlRRZXIyIiElgUXiyQHJlMx/COlHvKSclIsbocERGRgKLwYgHDMBjRcQSgriMREZHGUnixSFV4+eLQF5imaXE1IiIigUPhxSKDEwYT6gglqyiL3cd3W12OiIhIwPBpeFm9ejUTJkygffv2GIbBBx98UG/7lStXYhhGjWXXrl2+LNMSwfZgzk04F9At0yIiIo3h0/BSWFhI//79efHFFxu13e7du8nIyPAu3bt391GF1tIt0yIiIo3n8OXOx40bx7hx4xq9XVxcHFFRUU1fkJ8Z3qEyvHx97GtOlJwgKiTK2oJEREQCgF+OeRkwYACJiYmMHj2aFStW1Nu2tLSUvLy8akugSAxPpHt0dzymhy8Pf2l1OSIiIgHBr8JLYmIir776KvPmzWP+/Pn06NGD0aNHs3p13d0qM2bMwOVyeZekpKRmrPinG9Hh+7uONO5FRESkQQyzme7TNQyDBQsWcOWVVzZquwkTJmAYBgsXLqz19dLSUkpLS70/5+XlkZSURG5uLpGRkT+l5Gax6cgmJi+ZjCvYxaprVmG32a0uSUREpNnl5eXhcrka9PntV1deajN06FD27NlT5+vBwcFERkZWWwLJWe3OIjIoktzSXL4+9rXV5YiIiPg9vw8vqampJCYmWl2GzzhsDs5vfz6gu45EREQawqfhpaCggM2bN7N582YA0tLS2Lx5M+np6QA89NBDTJo0ydv++eef54MPPmDPnj1s376dhx56iHnz5nH33Xf7skzLjUiqHPey8uBKS+sQEREJBD69VXrDhg1cdNFF3p+nTZsGwOTJk5k9ezYZGRneIANQVlbG/fffz6FDhwgNDaVPnz4sWrSI8ePH+7JMyw3vMBy7YefbE9+SnpdOp8hOVpckIiLit5ptwG5zacyAH39y66e3sjZzLfcPvp/JfSZbXY6IiEizalEDdluLizpVXqFanr7c4kpERET8m8KLn7goqTK8bD66mZySHIurERER8V8KL36ifXh7esb0xGN6WHVwldXliIiI+C2FFz8yKmkUACsO1v9IBBERkdZM4cWPVI17WXN4DcXuYourERER8U8KL36kR3QP2rdpT0lFCWsOr7G6HBEREb+k8OJHDMPwXn1R15GIiEjtFF78TNVdR6sOrqLCU2FxNSIiIv5H4cXPDIwfSERQBMdLj7P56GaryxEREfE7Ci9+xmlzMqJj5bOOVqSr60hEROTHFF78UNUt08sPLqeFPb1BRETkJ1N48UPndzifIFsQB/MPsufEHqvLERER8SsKL36ojbMN57U/D4BlB5ZZXI2IiIh/UXjxU5d0uQSAz/Z/ZnElIiIi/kXhxU9dmHQhDpuDvbl72Xtir9XliIiI+A2FFz8VGRTJsMRhACw9sNTiakRERPyHwosfu6RzZdeRwouIiMgPFF782KhOo3AYDr45/g37c/dbXY6IiIhfUHjxY65gF0MShwCwLF13HYmIiIDCi98b03kMoLuOREREqii8+LlRnUZhN+zszNnJwbyDVpcjIiJiOYUXPxcdEs3ghMEALE3XwF0RERGFlwBQ1XW0dL/Ci4iIiMJLABjVaRQ2w8a27G0cLjhsdTkiIiKWUngJAG1D2zIofhCgOV9EREQUXgJEVdfRkrQlFlciIiJiLYWXAHFJ50uwG3a2ZW/jQN4Bq8sRERGxjMJLgIgNjWVo4lAAPkn7xOJqRERErKPwEkDGJY8DYHHaYkzTtLgaERERayi8BJDRnUYTZAsiLTeN3cd3W12OiIiIJRReAkh4UDgjk0YCsHjfYourERERsYbCS4AZnzwegE/2f4LH9FhcjYiISPNTeAkwwzsOJ9wZTmZhJqlZqVaXIyIi0uwUXgJMsD2YUZ1GAbrrSEREWieFlwB0WfJlAHy6/1PKPeUWVyMiItK8FF4C0JDEIcSExHCi9AQph1OsLkdERKRZKbwEIIfNwaVdLgUq53wRERFpTRReAlTVXUfL05dT7C62uBoREZHmo/ASoPq360+H8A4UuYtYnr7c6nJERESajcJLgDIMgwndJgCwcO9Ci6sRERFpPgovAWxi14kApGSkcKTwiMXViIiINA+FlwCWFJnEwLiBeEwPH+/72OpyREREmoXCS4Cb2K3y6svCvQv1pGkREWkVFF4C3JguYwi2B7Mvdx/bs7dbXY6IiIjPKbwEuIigCO/jAj789kOLqxEREfE9hZcW4IpuVwCVT5ouqyizuBoRERHfUnhpAYYmDiUuNI7c0lxWf7fa6nJERER8SuGlBbDb7FzWrfJhjR/uVdeRiIi0bAovLURV19GX331JTkmOxdWIiIj4jsJLC9Etqht9YvvgNt0s3qeHNYqISMul8NKCXHFG5dWX+d/O15wvIiLSYim8tCDjk8cTbA9mz/E9bD221epyREREfMKn4WX16tVMmDCB9u3bYxgGH3zwwSm3WbVqFYMGDSIkJISuXbvyyiuv+LLEFsUV7OKSzpcAMG/PPIurERER8Q2fhpfCwkL69+/Piy++2KD2aWlpjB8/nuHDh5OamsrDDz/MlClTmDdPH8QNdXX3qwH4JO0TCssLLa5GRESk6Tl8ufNx48Yxbty4Brd/5ZVX6NSpE88//zwAvXr1YsOGDTz33HNcffXVPqqyZRkUP4gukV3Yn7efT9I+4edn/tzqkkRERJqUX415WbNmDWPGjKm27tJLL2XDhg2Ul5fXuk1paSl5eXnVltbMMAzv1Zd53+iKlYiItDx+FV4yMzOJj4+vti4+Ph63282xY8dq3WbGjBm4XC7vkpSU1Byl+rWJZ0zEYXOwLXsbu3N2W12OiIhIk/Kr8AKVVw5OVnXL74/XV3nooYfIzc31LgcPHvR5jf4uJiSGUUmVD2t8/5v3La5GRESkaflVeElISCAzM7PauqysLBwOB7GxsbVuExwcTGRkZLVF4OozK7uOFu1bRLG72OJqREREmo5fhZdhw4axdOnSaus+++wzBg8ejNPptKiqwDQ0cSgdwjuQX57P0gNLT72BiIhIgPBpeCkoKGDz5s1s3rwZqLwVevPmzaSnpwOVXT6TJk3ytr/jjjs4cOAA06ZNY+fOnbz++uvMmjWL+++/35dltkg2w8ZV3a8CNHBXRERaFp+Glw0bNjBgwAAGDBgAwLRp0xgwYAB/+MMfAMjIyPAGGYDk5GQWL17MypUrOfvss3nqqaeYOXOmbpM+TVeecSV2w86mrE3sPbHX6nJERESahGG2sIfg5OXl4XK5yM3N1fgX4N7l97L84HKu63Edjwx9xOpyREREatWYz2+/GvMiTe+6ntcB8NG+jzTjroiItAgKLy3c0MShdInsQmF5IR/t/cjqckRERH4yhZcWzjAM79WXd3e9SwvrJRQRkVZI4aUVmNhtIqGOUPbm7mV95nqryxEREflJFF5agYigCCZ0nQDAu7vftbgaERGRn0bhpZWo6jpanr6czMLMU7QWERHxXwovrUT36O4Mih9EhVmh5x2JiEhAU3hpRaquvrz/zfuUV5RbXI2IiMjpUXhpRUZ3Gk270HZkl2SzLH2Z1eWIiIicFoWXVsRpc/LzM38OwNydcy2uRkRE5PQovLQy1/S4BqfNyddHv2Zz1maryxEREWk0hZdWpm1oW8YnjwfgrR1vWVyNiIhI4ym8tEI39r4RgGXpyzhUcMjiakRERBpH4aUV6hHTg6GJQ/GYHv61819WlyMiItIoCi+t1KTekwCYt2ceBWUFFlcjIiLScAovrdT5Hc6nq6srheWFzN8z3+pyREREGkzhpZWyGTbv2Je3d76N2+O2uCIREZGGUXhpxS7vejnRwdEcLjzM8vTlVpcjIiLSIAovrViII4RrelwDwJwdcyyuRkREpGEUXlq563peh9PmZMvRLaRmpVpdjoiIyCkpvLRybUPbMrHbRABmbZ1lcTUiIiKnpvAi/LrvrzEwWPXdKr45/o3V5YiIiNRL4UXoHNmZSzpfAujqi4iI+D+FFwHg1n63ArBk/xIO5h+0uBoREZG6KbwIAL1ie3F++/PxmB5mb5ttdTkiIiJ1UngRr1v63QLAB99+wLHiYxZXIyIiUjuFF/EaHD+Y/u36U+Yp07wvIiLitxRexMswDO/Yl/d2v0deWZ7FFYmIiNSk8CLVjOg4gjOizqCwvJB3d71rdTkiIiI1KLxINTbD5h37MmfHHArLCy2uSEREpDqFF6lhbJexdInsQm5pLu/sesfqckRERKpReJEaHDYHt591OwCzt81mxe6DfLj5EGv2ZlPhMS2uTkREWjvDNM0W9WmUl5eHy+UiNzeXyMhIq8sJWBWeCi5573KOln6HI2sEk3OLeNs9GocrkekTejO2b6LVJYqISAvSmM9vXXmRWi3dkcXBfecD4Ildy63OBcQZJ8jMLeHOuZtYsi3D4gpFRKS1UniRGio8Jk98tIPyvP54StvisZfyTmQEAFWX6Z74aIe6kERExBIKL1LDurQc3LkZ9DEO0DO7MwCzXRGc5dhBHyON3kYa7twM1qXlWFypiIi0Rg6rCxD/k5Vfwg2Oz5nqmE9FKVxZlsj+ICfJMR8xI/dtAJ53X0VW/kUWVyoiIq2RwovUEBcRwtPu0SytGATAWTkfsj8hkzddkaw4dgt5nrZkmVHMjAixuFIREWmN1G0kNQxJjsHhSmSHmcx2M5ktJy4nuaycPLsNV+xydpjJOFyJDEmOsbpUERFphRRepAa7zWD6hN4AGICBnSnHTwCwKTqbLo49TJ/QG7vNsK5IERFptRRepFZj+yby8q8GkuAKIcuMYmveWDqV2Cm22Rie/L7meREREctokjqpV4XHZF1aDln5JRTkfc4zac/iME0WnvsUSb1+ZnV5IiLSQmiSOmkydpvBsG6xXHF2B24YMYnznLG4DYOX1vwRPB6ryxMRkVZI4UUaZcrwpwFYZCth94aXLa5GRERaI4UXaZQ+SRdwaVhnTMPghS2vgLvU6pJERKSVUXiRRrtn1LPYTZNVQbBp9dNWlyMiIq2Mwos0WufYXlwVczYAf947D7PouLUFiYhIq6LwIqflzoueJdSEr4PsLFn2W6vLERGRVkThRU5Lu4hEbkm6FIC/Hk2hJPtbiysSEZHWQuFFTtvkEU+RYNrJcNh5a+m9VpcjIiKthMKLnLYQZyj39r0FgH8W7+fY/tUWVyQiIq2Bwov8JOMH3UU/WxuKbDZeWPUga/Zm8+HmQ6zZm02Fp0VN3iwiIn6iWcLLSy+9RHJyMiEhIQwaNIgvvviizrYrV67EMIway65du5qjVGkkm2Hj9+dNB2CBmcef5/6Je9/dzC9fS+GCPy1nybYMiysUEZGWxufh5d///jdTp07lkUceITU1leHDhzNu3DjS09Pr3W737t1kZGR4l+7du/u6VDlNmcVn0z0/EtMwCIpbzFTHe7TjOJm5Jdw5d5MCjIiINCmfh5e//OUv3HLLLdx666306tWL559/nqSkJF5+uf6p5ePi4khISPAudrvd16XKaajwmDzx0Q72HrmRII/J1jCDvpGfEmecoKrT6ImPdqgLSUREmoxPw0tZWRkbN25kzJgx1daPGTOGr776qt5tBwwYQGJiIqNHj2bFihW+LFN+gnVpOWTklpBbnkT340kA/F9sNA6jCAATyMgtYV1ajoVViohIS+Lw5c6PHTtGRUUF8fHx1dbHx8eTmZlZ6zaJiYm8+uqrDBo0iNLSUt566y1Gjx7NypUrGTFiRI32paWllJb+8HydvLy8pj0IqVdWfgntOE6ccYLiY6OIj3yDDKeDS9r9B3dWWGUbM4qs/BKLKxURkZbCp+GlimEY1X42TbPGuio9evSgR48e3p+HDRvGwYMHee6552oNLzNmzOCJJ55o2oKlweIiQrjB8TlTHfMB+DwnlKnx7VgZXcz8wul0cbt53n0VcRHjLK5URERaCp92G7Vt2xa73V7jKktWVlaNqzH1GTp0KHv27Kn1tYceeojc3FzvcvDgwZ9UszTOkOQYloWN5/LSP3JZ6R/5NPd6zi8qptwweDQ2kQmlT7IsbDxDkmOsLlVERFoIn4aXoKAgBg0axNKlS6utX7p0Keedd16D95OamkpiYmKtrwUHBxMZGVltkeZjtxncPfECtpvJ7DCT2e7pykPZx3GaJlvCDBIiU7h74gXYbbVfaRMREWksn3cbTZs2jRtvvJHBgwczbNgwXn31VdLT07njjjuAyisnhw4dYs6cOQA8//zzdOnShT59+lBWVsbcuXOZN28e8+bN83WpcprG9k3k5V8N5ImPdkAedHa76ZcTz6bYLPbHbWFEYqHVJYqISAvi8/By7bXXkp2dzZNPPklGRgZ9+/Zl8eLFdO7cGYCMjIxqc76UlZVx//33c+jQIUJDQ+nTpw+LFi1i/Pjxvi5VfoKxfRO5pHcCqdvbs2vbIW7v9Que2HwzGQ54dfGtTP3VCqhjnJOIiEhjGKZptqgJOPLy8nC5XOTm5qoLyWKfb53D1E3P4jBN3u39P/QY8j9WlyQiIn6qMZ/feraR+MzofpMYFdoRt2HwxNd/p6LwmNUliYhIC6DwIj718NhXCTdhq9PGu4tutbocERFpARRexKfiI5O478wbAPhb4R4ydn5ocUUiIhLoFF7E534+7PcMdERRbLPx1H8fwywrsrokEREJYAov4nM2w8b0S/6O0zT5wmmy5NMpVpckIiIBTOFFmkXXuLO4rePFADxz9CtOpK+xuCIREQlUCi/SbG696FnOMILJsdv532X3gKfC6pJERCQAKbxIs3HanTw98s/YTZNP7KUsWfZ7Nmzdya53HmLD1p1UeFrUlEMiIuIjzfJUaZEqfTqP5NZ2Q/nHsbU8/d0SOq8O5W3HS1z2dQdyIg8zfUJvxvat/TlWIiIioCsvYoEuHR+lU6lBrt2GPfEjqq63ZOaWcOfcTSzZlmFpfSIi4t8UXqRZVXhMXlm0npiMi3CYJqnhHj5uE0Zf2356G2n0MdJ4ceGX6kISEZE6qdtImtW6tBwuLlrMVMd8Xj0eyQsxUcyIjWFByevEV1QO4H2+6CrWpY1iWLdYi6sVERF/pPAizSorv4S33aNZWjEIW5ab7mGvsSfExu/bJnA8/XYqcJBlRpGcX2J1qSIi4qfUbSTNKi4ihKNEs91MZqvZnaDDlxHi8bApzE7H2EVsN5M5SjRxESFWlyoiIn5K4UWa1ZDkGBJdIRjf/5xf1onf5ZwAYE3bDIaGfk6iK4QhyTGW1SgiIv5N4UWald1mMH1CbwAMIMuM4tDxSzizIAy3YZDffgnTL2qD3WbUvyMREWm1FF6k2Y3tm8jLvxpIgquyC+lv7l+w9fC9RLshPchOys6pUOG2ukwREfFThmmaLeqe1Ly8PFwuF7m5uURGRlpdjtSjwmOyLi2HrPySyjEu5av5TcpjmIbBX2LP45LL/2F1iSIi0kwa8/mtKy9iGbvNYFi3WK44uwPDusUyrOfPuDnhAgAez/qCjB3zLa5QRET8kcKL+JW7xrxAX3sEeXY793/1GOV5h6wuSURE/IzCi/gVp83Jc+PnEGnC104bf15wLXg8VpclIiJ+ROFF/E6HmDP438EPAvA2uXz66b0WVyQiIv5E4UX80si+N3BLu3MB+EPmcvbuWMCGrTvZ9c5DbNi6U88+EhFpxXS3kfgtd0U5t/1rJBs8+XQp8xCSdgP/CfoTl5X+kZzIXkyf0JuxfROtLlNERJqA7jaSFsFhd3J5j78S5TbZH2QjKvE/VCXtzNwS7py7iSXbMiytUUREmp/Ci/itCo/JG8vS6XL4POymSUqkm7mREfS17ae3kUYfI40XF36pLiQRkVZG4UX81rq0HC4uWsxbFf/m/u+ff/RcTBRXRsxhUfAjfBz8CBcXLWZdWo61hYqISLNyWF2ASF2y8kt42z2apRWDMI96uMA5iy8jPdwf146eB8aQWdaNLDOK5PwSq0sVEZFmpCsv4rfiIiqffbTdTGaH2Y3vMibRr6SUPLuNIx0/JcsI5SjRlY8WEBGRVkPhRfzWkOQYEl0hVD1f2mMG83zWMWLcHg4E2enX4Xm6RHoYkhxjaZ0iItK8FF7Eb9ltBtMn9AbAALLMKP5VegWh303EaZqsD4cx8c9iRzPwioi0Jgov4tfG9k3k5V8NJMFV2YX0vPvn7Cq+gE7HRwPwjuM48z+40eIqRUSkOWmSOgkIFR6TdWk5ZOWXEBcRwpDkGF5Zdg+vZKzCYZq81OlKho162uoyRUTkNGmSOmlx7DaDYd1iueLsDgzrFovdZvA/l7zAZeFdcRsG0w4s4NvU2VaXKSIizUDhRQKWYRg8ecV7DHS4KLDZ+J9N/8ex/ausLktERHxM4UUCWpAjmL/9bAGdcZLhsPM/n99F7tHdrNmbzYebD7Fmb7Zm4BURaWE05kVahPSj27nx4+vIsUG/YvjuwF1cZV/L2+7ROFyJeoijiIif05gXaXU6tevDLV2nE+ox2RoK3Tq+zD2O+cQZJ/QQRxGRFkbhRVqECo/Jy19F4/ruMpymyYZwD3+MjcbE430S9RMf7VAXkohIC6DwIi3CurQc3LkZBBUlcU5GLwzT5D+REfSJm0MfYx+9jTTcuRl6iKOISAugBzNKi5CVX8INjs+Z6pgPpfBedjhPtY1hSUwp95t/YnJePs+7ryIr/yKrSxURkZ9I4UVahLiIEJ7+/gnUAH3L93OP7d+8EBPFc7HRbK/oyorsUczUQxxFRAKeuo2kRRiSHIPDlcgOM5ntZjLbPF24PTePgdlxAHwSd5yRce8ypEu0xZWKiMhPpfAiLcKPH+JY5ejRKzkjpxMAn8Uc4OOPfg0ta3YAEZFWR+FFWoyTH+KYZUbxvPsqjprRZJTcx9igXpiGwR9ObGTRQgUYEZFApknqpMWp7SGONgOeXHg975/Yhs00eTJqEFdcMZsKkxpt7Tbj1G8iIiJNqjGf3wov0mp4TA9PLryeeSe2Y5gmdzp6Myf9djLySr1tEl0hmo1XRMQCmmFXpBY2w8YfJv6LX0afhWkYvFSxkwHOZ2lHDlMd79OO45qNV0QkACi8SKtiM2z8/rK36J3XBYAv4g5zQdtXmfr9owQ0G6+IiP9TeJFWZ/3+46w99BvOzO4CwLJ2J5gZ7cLEA4AJZOSWaDZeERE/pfAirU5WfgntOEHJ0Us551gCAK9FuUhOfJ2zjG/oY6TRjuNk5ZdYXKmIiNRGM+xKqxMXEfLDowTy4T3C+WNsNKtdFVzseJFnjh7j5fKriIsYZ3WpIiJSC4UXaXWGJMfwx7DxLMsfhEnlowT+XDGX38e1ZVmbMH5t64gjZyD3JMdYXaqIiNSiWbqNXnrpJZKTkwkJCWHQoEF88cUX9bZftWoVgwYNIiQkhK5du/LKK680R5nSSthtBndPvIDtZjI7vn+UwMVFxfQ9OIwwj8nWUBsFca9wNO1zq0sVEZFa+Dy8/Pvf/2bq1Kk88sgjpKamMnz4cMaNG0d6enqt7dPS0hg/fjzDhw8nNTWVhx9+mClTpjBv3jxflyqtyMmz8VbJLupPzLFbifHAHqeNG1ZOYefGVy2sUkREauPzSerOPfdcBg4cyMsvv+xd16tXL6688kpmzJhRo/0DDzzAwoUL2blzp3fdHXfcwZYtW1izZs0p30+T1EljVHhMUrfvInzbHAr6TmJAn54cOb6Huz7+Jd9SRqjHw7MdL2PkxX8CQzPvioj4it9MUldWVsbGjRsZM2ZMtfVjxozhq6++qnWbNWvW1Gh/6aWXsmHDBsrLy2u0Ly0tJS8vr9oi0lB2m8Hgfr3o+csZDO7XC7vNoH3smcy5ZhnDHDEU22xMObSYt+ddAxVuKjwma/Zm8+HmQ6zZm625YERELODT8HLs2DEqKiqIj4+vtj4+Pp7MzMxat8nMzKy1vdvt5tixYzXaz5gxA5fL5V2SkpKa7gCk1YoIjebv1y3l6sgeeAyDZwp38dDsEVzyzIdMee0T0t5/lCmvfcIFf1qu2XhFRJpZswzYNX50ud00zRrrTtW+tvUADz30ELm5ud7l4MGDTVCxCDjtQUy/8j/c1/FSDNPkY0c+sTGP0d2x2zsjrx4nICLS/HwaXtq2bYvdbq9xlSUrK6vG1ZUqCQkJtbZ3OBzExsbWaB8cHExkZGS1RaSpGIbB5IuepXv25bTxmOwKhczk+WwPCgLQ4wRERCzg0/ASFBTEoEGDWLp0abX1S5cu5bzzzqt1m2HDhtVo/9lnnzF48GCcTqfPahWpy7q0HNKP9iV5/zg6lnk46rAxOTGOc6Leo4+xj95GGu7cDD1OQESkmfi822jatGn885//5PXXX2fnzp3cd999pKenc8cddwCV3T6TJk3ytr/jjjs4cOAA06ZNY+fOnbz++uvMmjWL+++/39elitQqK7+EGxyf847xKu8dPsSIomJKbTbmJRxnSPs/Mz/kEW5wfK7HCYiINBOfz7B77bXXkp2dzZNPPklGRgZ9+/Zl8eLFdO7cGYCMjIxqc74kJyezePFi7rvvPv7+97/Tvn17Zs6cydVXX+3rUkVqFRcRwtPu0SytGARAn+/2cWe793klKpL3IyPYHBxG6HdxnBsRcoo9iYhIU/D5PC/NTfO8SFOr8Jhc8KflZOaWYAJ9jDQWBT/CjY5fsK99Cnl2g/AKD0+1v4SLx/wFbHreqYhIY/nNPC8iLYHdZjB9Qm8ATr7fLafwbPL23UenYicFdhv3Hfmc/507kpK8QwCaE0ZExEd05UWkgZZsy+CJj3bgzs3gBsfnvO0ejcOVyKOXdWdn+h94M3sjAGe4PdzYYQrPpp5Ro+30Cb0Z2zfR4iMREfE/jfn8VngRaYQKj8m6tByy8kuIiwhhSHIMdlvl9Zgvt73NI+ufIccGQR6Tgcc6k5Ezho+D/8BlpX9kh5kMwMu/GqgAIyLyI+o2EvERu81gWLdYrji7A8O6xXqDC8AFfW/gPz9bxJnFYZTZDFLi0olK+idZdjugOWFERJqKwotIE9qb3YYD++9mSFZngjwmW9rAzzokMChqHr2NvZoTRkSkCSi8iDShrPwSfuVYzqzCL3jvcAZ9SkvJs9tZkHCMM5P+xpzQxzQnjIjIT+TzeV5EWpNqc8KUQt+ib7mo3TxeiXLxeZswNoYEMzDrKOeG6e8GEZHTpfAi0oSGJMfgcCWyIze6coyLB/50Io+VuT/neOJyDgXD8sQDlH45jk62Z+hwxlig/oHAIiJSncKLSBOqmhPmzrmbqs0Jk1fSjd37RnJ227c40HY3/7VX8LMvfsvdW94gruuTPLHkO+9t1U/rtmoRkXrp2rVIExvbN5GXfzWQBFcIWWYUz7uvIsuMIsEVwW/Gvsi8sXMYbIug2Gbj2YId/GP9VXQoX0SccYKpjvnEGSfIzC3hzrmbWLItw+rDERHxO5rnRcRH6usK8pge5n35R/6y598U2CvXDc0L4k/H93Fj8VNsN5MxgARXCF8+MEpdSCLS4jXm81vdRiI+UjUnTG1sho2O7f8H+5IoBsTPJdVVREpkGZe3ac+F2e/gyLkaN0Fk5UaxLi2nzv2IiLRG6jYSsUhWfgk/NzYxJ2cXbx3OpGdpGfl2Gx/F5WHr+g8eiXqKGxzLdFu1iMiP6MqLiEV+fFt1v4K9XB3zHi9ER/FtUBC/SYjj7IiN9Dr+KXCz1eWKiPgNXXkRsYj3tmozme1mMls93bguv4B2e39F7+MJ2E2TzW3ggQN/4am3RnA0/SugcizNhq072fXOQ2zYulOPGhCRVkdXXkQsUtdt1eWeCLZkTiU6O41zzvgPKUYO73mOs/Dz25ho68iaw7/CyMtlUfBLXPZ1B3IiD+u2ahFpVXTlRcRCdd9WHcL/Xns1r01exRtDn6K/EUaJzcZ7HCY3/hm6tv0PRUZl5NFt1SLS2uhWaRE/cKoZdt0VHm75691kuVbzXVDl+piKCobmRLEnZyJlZjhExPPhgz/XbdUiEpB0q7RIgKnvtmqA9fuPM+BEMfcUHGRReBtejorkO6eTxe3yiYmZw80n8sg/fgHr0kbV2I8ePSAiLY3Ci0gAyMov4e2T7kzqf3wPt0f/h5ejoslw2nkuNpqoqK8p+HIyvSP+D1dcbwCWbMvgiY92kJH7w+3Wia4QjZERkYCmMS8iASAuIoSjRLPde2dSd35WUEjQ3ts4I2Mg7crhhN3O2xxgzKJf8Od3LuWj1R9x59xNZOSW0I7jTHW8TzuOa4yMiAQ8hReRADAkOYZEVwg/7uwxcZB64hrSvn2a3tkj6G46KbLZmF12mOn7HuLCDo/TK2RttecmVQ1ye+KjHbrNWkQCksKLSACouq0awIBqdyZVBhoHvx7zKPMmb+Tv/afS1wyl3DDYEFnCd8kLiOz0D74IDcGgAgATyMgtYV1aTrX3qfCYrNmbzYebD7Fmb7bCjYj4Jd1tJBJAGjqG5cPNh3jtw5lExy7j6/BSPN/fVp1UVsEZJxI5emIE31Z049HrLuKKszs0at8iIr6gu41EWqixfRO5pHfCKe8eiosI4eLyLKYe+5ZDJ+z8KzKC+RHhHAyyczAui9C27zE8H5zZReC5lSU7jnDn3E2YQDuOc4Pjc952jyYzN5o7527i5V8NVIAREb+hKy8iLVCFx+SKZ96H/COYQF/bfv4Q9E8eDzubbVHZfBf0Q9uz3Aau3DP579GJ5Jqx9DHSWBT8CJeV/pHtZjIGkOAK4csHRukWaxHxGV15EWnl7DaDuydewJ1zN1Wu8EAb02RHzs/Zld2F5LAUenT+LynmUb52ALG7CYv+EwPyI3Gc6Ivp+WFfJ4+PqW8uGhGR5qIBuyIt1MmPHjhZgiuU3191Fy9PXsHSny3m2pBzSCgzKbLZ2OgqYG3nFK7okEiftnMZHrSaPkYa7ThOVn5Jtf1ocK+IWEXdRiItXIXHJHX7LsK3zaGg7yQG9OlZrftnzd5sUt74LReEL+b9iHCWh4VSYqv8u8YwTc4tKeGMvBiGjXmZEWcPAn4Y3OvOzfCOj3G4EjW4V0ROW2M+vxVeRFq5H4+P6e/YzmDXh/w7PIYdoT+EnCCPyQhbG/qEn8fMDYPIM6OrjY/ZYSYDaHCviJwWjXkRkQarMT7GDf9b8C9mZT9MkMOgW9SnFEUf4IDdwzKKWFawjNAzP6N/YSgR+Z0pLqsMOCaVc9A88dEOLumdUGNwr56xJCJNReFFRLzjY574aAfk/bA+KKwnN196FZf2SeCbAyt5N+UlVhXs5KjTxuaIUoj4hpGeDpxV9A+65nfhaP5g9uZ2qzG498fdTE+rm0lEfgJ1G4mI16nGx3y4+RD73n+Ei8MWsbRNGJ+1CeOQ84e/gRymSd+SCgZEDODa826lQ5eLWLI90zuHjLqZRKQu6jYSkdNitxkM7tcL+s2o9fW4iBCedl/MsvzBkA9n2fbxlzZzeDW0G9+EF3IwyGBzqIPN7q28sfpeui03iS+MZWCb/mwrHFFtX6fqZhIRqYvCi4g02JDkGByuRHbkRlc+4NEDvcvK2ZN/IzuOJNPOuY9esV9giznAZk8hex0Ge1054FpBtOdz4otsvFcSzmBSoLQyvmTlRtXoZjrVFSARad0UXkSkwaoeEHnn3E01nnBtAMfKu3L9xT9nbN9EcguPMGfpC+z4biHbw9wct9tZHw7rw2Og7RaSyjcwrLiEkMIOZBxuD91GAT+Mj4nJ28mi4Je47OsO5EQe1vgYEfFSeBGRRjl5cG9W7g9Pt0740UMcXW3iGdzvPuak9KSdkU3X0J20a5PK0TY5bAkJ5qDTyUGnEyLzYN+9/GsP9LInsOdQJ0oLh1V7z8zckjqfsaS7mERaHw3YFZHT0pDQUOExueBPy8nMLak2YPeK8kdwhx3E1WY7J9oc42BQzf8NdSmtYGhpEaWF3UgrGszx8o4QkcCHD/7c+z6aLE+k5dAkdQovIn5jybYM7xwyveu422hwx1I+/Go2m79dwIHQUtKCnDX2k+B2073YRu+4QVzYcwwH3YP5n/f2NuouJl2lEfFfuttIRPxGQ7uZ2ra/jZTVZxBnnKCnPZse4f8lPOwb1ga3IS3YINPhIDMCvihO5R+pqQR5TAYkG0QWRxNWEsMBtwNKK+q8i0lzzYi0HLryIiLN4lRXPdbszeaXr6V4fz75asoe2tE1bAPRYTtpE5vNLjOf3FqumIRXeOhcaiOmJJyyko78fPh1jBl6OZ/tyjmtuWZ0pUak+ejKi4j4HbvNqHY79I8NSY4h0RXiHR9zsjIznN2FF5LgGMuXk0bx0ZZD7Fl4Dz3DUtgaHMz24CB2BQVRYLexPQwIKwB2sXbv4/xhzx/oVGbjwsRI3KWJBJdEU2Se+pEGulIj4r8UXkTEL/z4Nuws84cupqpIMX1Cb+w2g/jIUP5YfDVxJaMB6Gvbz2znazxhG8vR4CLKQ46SHVLE4SAPxTYbu0OAkDyqnn1wLkl0KH+J4aVOIsrCKS1tzydfHGbMOeMJCov1jtOpvFJzgqmO+SytGMSO3Oh673rS3DQizUPhRUT8xsnjYzJyo3ne/XMAEn80Pqa2yfKcQGrxcLYXJWMACa4Qvrx/OO99+TH71/2VNiHpfBPkZE+QkyyHg0NOO4ecHioDTR7r9u/ikbQ/0dEDUaVBjIx3UVaWQFhpG05gA+q+UtPYuWka0x2lriuRmhReRMSvjO2byCW9E+r9wD7VZHlQeZUm2BnEGZ1GMvPTIuKMEwAMtu3nweBZ/Nk2gmPBJZQFn+B4UDGZwR4KbAbpdkgPK4ewY8AxAIbTEVfFywwqN4gqC8JWFs2cj5cwpNs57CvswpT5WZgYxJxUTF1z0zSmO6qqbUZuiXfdj4OcSGukAbsiErAaMs9LXXPNXFb6R7abP1yl+eL3F3H8xF4+TFnEdzvfxRmcSZrTyQGng0xH/X/nRVZ4iCs3aFtuo2/FCY6UJpNTnkRxWRx5QWfz/kM3YrcZP+qOqn/g8Mlt23Hce3zHiK7RVqQl0IBdEWkVql+luYiZP+EqjcNuo11sd/r0vJF/fNHWe6VmoG0/04P+yf8ylqwgN0ZQDkVBhVS0cXOYUrLtBnl2G3l2+DbEJAUXkPP9Aob5GWNm/4n2RhC2Yicj49tQUR5NG3cQu3DSxp2N6e6Mgc3bHQWVXVNVf1nGnTTu5qgZrQdaSqun8CIiAe1UdzFBw+eagdrH04SZJqmlF7C9+KTxNHeN4uOvD/N/731M1+DthDmPEBV0kIjgw3xjj+CY08NRh0GJzSDLbpCFG9q4oU0xVd1R/yUReJ+2nv8Q6/YQWWHnt3NcxDhcdHfY6RwZS6G7La4KKDF+CCkmkJFbUuOBliKthcKLiLQKDblKAw2/UmO3GcRFhHDI05FDxR2h+OSuoPu/7woyibAf5YlLnWRk7+TIvs8Icx7lsMPOEYedTIeDHLudUpvB4SA7h4Fd5EJFLsQBpHnf+xySCK34B9HuKOwVoZSXu3hjVwrbizoTExJDbEhs5dfQWKJDogl1hPruH1PEYgovItJqNOQqDTT8Sk19c9MAGBiEh3fiigtGsS4thylre3m7o/ra9vNv52s84L6Jg7YQQpzHKHcUM+CMIE6UHiMzdz8ljlKO2u0cs9spsdkotgP2E7g5AWSw5tgu1hyr/RhCHaFEB0cTHfL9EhxNVEgUUcE/LK5gl/erK9hFiD0Ew1A3lPg/hRcRkVqcznia+uamqa07CmBbRXe2u5Mxyiq7o2ZfPQqAK555H/KPYAMusu3j0eDXmW5exde2BDz2Iira2PnZ+UlklxwjpySHnJIcskuyySnOocxTRrG7mGJ3MYcLDzf4mINsQd4gExkUWbkERxIRFOH9OTwonIigCCKcEZXff/81PCgcp63mM6lEfEHhRUSkDo0dT1Pf3DSN6Y4CuHviBd4HWuKBSI/JN6UD2Vd1Z9LE2u82Mk2TIncROSU5HC857v16ovQEx0uPk1uaS05JDnmleZwoPcGJ0hPklebhNt2Ueco4WnyUo8VHT+vfK9geTLizMsi0cbYh3Fn5tWoJc4YR5gj74WdHmHddmDOMUEcoYY4wQp2VXx02fURJ7Xx6q/Tx48eZMmUKCxcuBGDixIm88MILREVF1bnNTTfdxJtvvllt3bnnnktKSkodW1SnW6VFxAoNnUyuIbd3/7ht5eR3lbdV50T2avJ5XkzTpLC8kLyyPHJLc8krqww2+WX55JXlVX4tzav8vjyfgrIC8su+/1qeT7G7uMlqOZnT5iTEEfJDqHGEEuIIIcQeUvn1+9eC7cHV1gfbgwmxhxDs+P6rPbhy+f7nIHsQwfZg79dgezBOm1NdZhZrzOe3T8PLuHHj+O6773j11VcBuP322+nSpQsfffRRndvcdNNNHDlyhDfeeMO7LigoiJiYmAa9p8KLiPi7xs6w6++PHXB73BSWF1YGmvICCssLvUtBeQFF5UXV1hWWF1LsLqbIXeR97eSfK8wKS44jyPZDqKlanDZn5fe273+2OyvX2X54vaqN0+bEYXN421QtDpuj8nv7998b339vOHDY6lhOes1u2L37sNvs2I3KpaWFLb+Y52Xnzp0sWbKElJQUzj33XABee+01hg0bxu7du+nRo0ed2wYHB5OQkOCr0kRELNXQgcNVbQf36wX9Zvi4qtPnsDm8Y2V+KtM0KfeUU1ReRElFCUXuosrxO+XFlFSUUOIu8Y7nKXGXUFpRSrG7mNKKUkrcJZRUVK4rdZd625dWlNZYyirKKK0orfbeZZ4yyjxlUP6TD6NZOAwHdpu9WsCxG3ZvwHHYHNgMmzfsnBx8bIbth9dtJ60zftjGZrN511d9rfreaXNy/zn3W3fsvtrxmjVrcLlc3uACMHToUFwuF1999VW94WXlypXExcURFRXFyJEj+eMf/0hcXJyvShURET9hGIb3qoevVQWlqjBTFWhKK0op95RXrvOUeV+rWnfy13JPOeUV5d52bo/bu77q56p1tX11e9y4TXfNdd8vFWZFnVei3KYbd4W7RghrDkG2oJYZXjIzM2sNHHFxcWRmZta53bhx4/jFL35B586dSUtL47HHHmPUqFFs3LiR4ODgGu1LS0spLf3hxOXl5TXNAYiISIvWnEHpp/CYHio8Fd6QU/V9hacy2FR4Kig3y/F4PFSYP7x2cvjxeDze9R6z8nuP6cHtqfzqMT3efVWYFd6fa/3qqcBus1v6b9Lo8PL444/zxBNP1Ntm/fr1ALX2x5mmWW8/3bXXXuv9vm/fvgwePJjOnTuzaNEirrrqqhrtZ8yYccp6REREApXNsGGz23CiW9GrNDq83H333Vx33XX1tunSpQtff/01R44cqfHa0aNHiY+Pb/D7JSYm0rlzZ/bs2VPr6w899BDTpk3z/pyXl0dSUlKD9y8iIiKBpdHhpW3btrRt2/aU7YYNG0Zubi7r1q1jyJAhAKxdu5bc3FzOO++8Br9fdnY2Bw8eJDGx9tsCg4ODa+1OEhERkZbJ5qsd9+rVi7Fjx3LbbbeRkpJCSkoKt912G5dffnm1wbo9e/ZkwYIFABQUFHD//fezZs0a9u/fz8qVK5kwYQJt27blZz/7ma9KFRERkQDis/AC8Pbbb9OvXz/GjBnDmDFjOOuss3jrrbeqtdm9eze5ubkA2O12tm7dyhVXXMGZZ57J5MmTOfPMM1mzZg0RERG+LFVEREQChE8nqbOCJqkTEREJPI35/PbplRcRERGRpqbwIiIiIgFF4UVEREQCisKLiIiIBBSFFxEREQkoCi8iIiISUBReREREJKAovIiIiEhAafSzjfxd1Zx7eXl5FlciIiIiDVX1ud2QuXNbXHjJz88H0JOlRUREAlB+fj4ul6veNi3u8QAej4fDhw8TERGBYRintY+8vDySkpI4ePBgi33EQEs/Rh1f4Gvpx9jSjw9a/jHq+JqWaZrk5+fTvn17bLb6R7W0uCsvNpuNjh07Nsm+IiMjW+R/kCdr6ceo4wt8Lf0YW/rxQcs/Rh1f0znVFZcqGrArIiIiAUXhRURERAKKwkstgoODmT59OsHBwVaX4jMt/Rh1fIGvpR9jSz8+aPnHqOOzTosbsCsiIiItm668iIiISEBReBEREZGAovAiIiIiAUXhRURERAJKqw0vL730EsnJyYSEhDBo0CC++OKLetuvWrWKQYMGERISQteuXXnllVeaqdLGmzFjBueccw4RERHExcVx5ZVXsnv37nq3WblyJYZh1Fh27drVTFU33OOPP16jzoSEhHq3CaTzB9ClS5daz8ddd91Va3t/P3+rV69mwoQJtG/fHsMw+OCDD6q9bpomjz/+OO3btyc0NJQLL7yQ7du3n3K/8+bNo3fv3gQHB9O7d28WLFjgoyOoX33HV15ezgMPPEC/fv1o06YN7du3Z9KkSRw+fLjefc6ePbvWc1pSUuLjo6ndqc7hTTfdVKPWoUOHnnK/gXAOgVrPhWEYPPvss3Xu05/OYUM+FwLp97BVhpd///vfTJ06lUceeYTU1FSGDx/OuHHjSE9Pr7V9Wloa48ePZ/jw4aSmpvLwww8zZcoU5s2b18yVN8yqVau46667SElJYenSpbjdbsaMGUNhYeEpt929ezcZGRnepXv37s1QceP16dOnWp1bt26ts22gnT+A9evXVzu+pUuXAvCLX/yi3u389fwVFhbSv39/XnzxxVpf/7//+z/+8pe/8OKLL7J+/XoSEhK45JJLvM8qq82aNWu49tprufHGG9myZQs33ngj11xzDWvXrvXVYdSpvuMrKipi06ZNPPbYY2zatIn58+fzzTffMHHixFPuNzIystr5zMjIICQkxBeHcEqnOocAY8eOrVbr4sWL691noJxDoMZ5eP311zEMg6uvvrre/frLOWzI50JA/R6ardCQIUPMO+64o9q6nj17mg8++GCt7X//+9+bPXv2rLbuN7/5jTl06FCf1diUsrKyTMBctWpVnW1WrFhhAubx48ebr7DTNH36dLN///4Nbh/o5880TfPee+81u3XrZno8nlpfD6TzB5gLFizw/uzxeMyEhATzmWee8a4rKSkxXS6X+corr9S5n2uuucYcO3ZstXWXXnqped111zV5zY3x4+Orzbp160zAPHDgQJ1t3njjDdPlcjVtcU2ktmOcPHmyecUVVzRqP4F8Dq+44gpz1KhR9bbx53P448+FQPs9bHVXXsrKyti4cSNjxoyptn7MmDF89dVXtW6zZs2aGu0vvfRSNmzYQHl5uc9qbSq5ubkAxMTEnLLtgAEDSExMZPTo0axYscLXpZ22PXv20L59e5KTk7nuuuvYt29fnW0D/fyVlZUxd+5cbr755lM+bDRQzt/J0tLSyMzMrHaOgoODGTlyZJ2/k1D3ea1vG3+Rm5uLYRhERUXV266goIDOnTvTsWNHLr/8clJTU5unwNO0cuVK4uLiOPPMM7ntttvIysqqt32gnsMjR46waNEibrnlllO29ddz+OPPhUD7PWx14eXYsWNUVFQQHx9fbX18fDyZmZm1bpOZmVlre7fbzbFjx3xWa1MwTZNp06ZxwQUX0Ldv3zrbJSYm8uqrrzJv3jzmz59Pjx49GD16NKtXr27Gahvm3HPPZc6cOXz66ae89tprZGZmct5555GdnV1r+0A+fwAffPABJ06c4KabbqqzTSCdvx+r+r1rzO9k1XaN3cYflJSU8OCDD3L99dfX+7C7nj17Mnv2bBYuXMg777xDSEgI559/Pnv27GnGahtu3LhxvP322yxfvpw///nPrF+/nlGjRlFaWlrnNoF6Dt98800iIiK46qqr6m3nr+ewts+FQPs9bHFPlW6oH/8Fa5pmvX/V1ta+tvX+5u677+brr7/myy+/rLddjx496NGjh/fnYcOGcfDgQZ577jlGjBjh6zIbZdy4cd7v+/Xrx7Bhw+jWrRtvvvkm06ZNq3WbQD1/ALNmzWLcuHG0b9++zjaBdP7q0tjfydPdxkrl5eVcd911eDweXnrppXrbDh06tNqA1/PPP5+BAwfywgsvMHPmTF+X2mjXXnut9/u+ffsyePBgOnfuzKJFi+r9kA+0cwjw+uuvc8MNN5xy7Iq/nsP6PhcC5few1V15adu2LXa7vUYqzMrKqpEeqyQkJNTa3uFwEBsb67Naf6p77rmHhQsXsmLFCjp27Njo7YcOHWr5XwgN0aZNG/r161dnrYF6/gAOHDjAsmXLuPXWWxu9baCcv6o7xRrzO1m1XWO3sVJ5eTnXXHMNaWlpLF26tN6rLrWx2Wycc845AXFOofJqYOfOneutN9DOIcAXX3zB7t27T+t30h/OYV2fC4H2e9jqwktQUBCDBg3y3r1RZenSpZx33nm1bjNs2LAa7T/77DMGDx6M0+n0Wa2nyzRN7r77bubPn8/y5ctJTk4+rf2kpqaSmJjYxNU1vdLSUnbu3FlnrYF2/k72xhtvEBcXx2WXXdbobQPl/CUnJ5OQkFDtHJWVlbFq1ao6fyeh7vNa3zZWqQoue/bsYdmyZacVmk3TZPPmzQFxTgGys7M5ePBgvfUG0jmsMmvWLAYNGkT//v0bva2V5/BUnwsB93vo0+HAfurdd981nU6nOWvWLHPHjh3m1KlTzTZt2pj79+83TdM0H3zwQfPGG2/0tt+3b58ZFhZm3nfffeaOHTvMWbNmmU6n03z//fetOoR63XnnnabL5TJXrlxpZmRkeJeioiJvmx8f41//+ldzwYIF5jfffGNu27bNfPDBB03AnDdvnhWHUK/f/va35sqVK819+/aZKSkp5uWXX25GRES0mPNXpaKiwuzUqZP5wAMP1Hgt0M5ffn6+mZqaaqamppqA+Ze//MVMTU313m3zzDPPmC6Xy5w/f765detW85e//KWZmJho5uXlefdx4403Vrsj8L///a9pt9vNZ555xty5c6f5zDPPmA6Hw0xJSfGr4ysvLzcnTpxoduzY0dy8eXO138nS0tI6j+/xxx83lyxZYu7du9dMTU01f/3rX5sOh8Ncu3Ztsx+fadZ/jPn5+eZvf/tb86uvvjLT0tLMFStWmMOGDTM7dOjQIs5hldzcXDMsLMx8+eWXa92HP5/DhnwuBNLvYasML6Zpmn//+9/Nzp07m0FBQebAgQOr3UY8efJkc+TIkdXar1y50hwwYIAZFBRkdunSpc7/eP0BUOvyxhtveNv8+Bj/9Kc/md26dTNDQkLM6Oho84ILLjAXLVrU/MU3wLXXXmsmJiaaTqfTbN++vXnVVVeZ27dv974e6OevyqeffmoC5u7du2u8Fmjnr+pW7h8vkydPNk2z8jbN6dOnmwkJCWZwcLA5YsQIc+vWrdX2MXLkSG/7Kv/5z3/MHj16mE6n0+zZs6dlYa2+40tLS6vzd3LFihXeffz4+KZOnWp26tTJDAoKMtu1a2eOGTPG/Oqrr5r/4L5X3zEWFRWZY8aMMdu1a2c6nU6zU6dO5uTJk8309PRq+wjUc1jlH//4hxkaGmqeOHGi1n348zlsyOdCIP0eGt8flIiIiEhAaHVjXkRERCSwKbyIiIhIQFF4ERERkYCi8CIiIiIBReFFREREAorCi4iIiAQUhRcREREJKAovIiIiElAUXkRERCSgKLyIiIhIQFF4ERERkYCi8CIiIiIB5f8Bjpjuqy/zhzgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "xx = np.linspace(3, 13, 21)\n",
    "yy = -0.5  + 2.85 * np.exp(-0.3*xx) + np.random.normal(size=len(xx), scale=0.005)\n",
    "\n",
    "mod = Model(expfunc)\n",
    "pars = mod.make_params(offset=-0.1, amplitude=0.2, decay=-0.1)\n",
    "result = mod.fit(yy, pars, x=xx)\n",
    "\n",
    "print(result.fit_report())\n",
    "\n",
    "plt.plot(xx, yy, 'o', label='data')\n",
    "plt.plot(xx, result.best_fit, '+-', label='fit')\n",
    "\n",
    "xpred = np.linspace(.25, 20.25, 101)\n",
    "ypred = result.eval(x=xpred)\n",
    "\n",
    "plt.plot(xpred, ypred, label='predicted')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c742bff1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17bdd2110>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "dy_dscale001 = result.eval_uncertainty(x=xpred, sigma=2, dscale=0.001)\n",
    "\n",
    "dy_dscale333 = result.eval_uncertainty(x=xpred, sigma=2, dscale=0.333)\n",
    "\n",
    "# and compare with uncertainties package\n",
    "u = result.uvars\n",
    "dy_umath = []\n",
    "for ox in xpred:\n",
    "    ux = u['offset'] + u['amplitude'] * umath.exp(u['decay']*ox)\n",
    "    dy_umath.append(ux.s)\n",
    "dy_umath = 2*np.array(dy_umath)\n",
    "\n",
    "\n",
    "plt.plot(xpred, dy_umath, label=r'2-$\\sigma$ band, uncertainties')\n",
    "plt.plot(xpred, dy_dscale001, label=r'2-$\\sigma$ band, dscale=0.001')\n",
    "plt.plot(xpred, dy_dscale333, label=r'2-$\\sigma$ band, dscale=0.333')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8ef17d4",
   "metadata": {},
   "source": [
    "...also very, very close.\n",
    "\n",
    "\n",
    "Let's go back to that original data.  It presents as 25 data \"observations\", but really has 4 independent x values for the model to be evaluated at.  This might be expressed as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ef9527c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ErrorbarContainer object of 3 artists>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([1.147058824, 1.105700713, 1.061177816, 0.996137132])\n",
    "y = np.array([6.6012e-05,  4.9955e-05, 3.2114e-05, -9.5747e-05])\n",
    "dy = np.array([3.7395e-05, 1.6015e-05, 2.7044e-05, 2.6871e-05])\n",
    "\n",
    "plt.errorbar(x, y, yerr=dy, linewidth=0., elinewidth=1, marker='+', label='data')\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4b832a87",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[Model]]\n",
      "    Model(expfunc)\n",
      "[[Fit Statistics]]\n",
      "    # fitting method   = leastsq\n",
      "    # function evals   = 187\n",
      "    # data points      = 4\n",
      "    # variables        = 3\n",
      "    chi-square         = 0.05494179\n",
      "    reduced chi-square = 0.05494179\n",
      "    Akaike info crit   = -11.1511016\n",
      "    Bayesian info crit = -12.9922185\n",
      "    R-squared          = 0.99662934\n",
      "[[Variables]]\n",
      "    offset:     6.3505e-05 +/- 8.8375e-06 (13.92%) (init = 0.0001)\n",
      "    amplitude: -3523190.54 +/- 18920125.7 (537.02%) (init = -9000)\n",
      "    decay:     -23.9132155 +/- 5.43632420 (22.73%) (init = -20)\n",
      "[[Correlations]] (unreported correlations are < 0.100)\n",
      "    C(amplitude, decay)  = +1.0000\n",
      "    C(offset, decay)     = +0.9222\n",
      "    C(offset, amplitude) = +0.9201\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17bda0790>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# and now we can try to fit that using 4 values with uncertainties:\n",
    "\n",
    "mod = Model(expfunc)\n",
    "pars = mod.make_params(offset=1.e-4, amplitude=-9000, decay=-20)\n",
    "result = mod.fit(y, pars, x=x, weights=1.0/dy)\n",
    "\n",
    "print(result.fit_report())\n",
    "\n",
    "plt.errorbar(x, y, yerr=dy, linewidth=0., elinewidth=1, marker='+', label='data')\n",
    "plt.plot(x, result.best_fit, '-', label='fit')\n",
    "\n",
    "xpred = np.linspace(.95, 1.3, 100)\n",
    "ypred = result.eval(x=xpred)\n",
    "\n",
    "plt.plot(xpred, ypred, '--', label='projected')\n",
    "\n",
    "dypred = result.eval_uncertainty(x=xpred, sigma=2, dscale=0.001)\n",
    "\n",
    "plt.fill_between(xpred, ypred-dypred, ypred+dypred,\n",
    "                 color=\"#DD9DAB22\", label=r'2-$\\sigma$ uncertainty band')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a81217d",
   "metadata": {},
   "source": [
    "now, with only one degree of freedom. The fit more clearly shows the extremely high correlations.  It is more obvious that the uncertainties are extremely large for the extrapolated values.  The plot here also makes it clearer that the amplitude term can be positive.    \n",
    "\n",
    "\n",
    "My conclusions here are:  \n",
    "\n",
    "   1. we should lower the default step for the derivative in `ModelResult.eval_uncertainty` to 0.001 for more stability, especially for pathological cases like this one.\n",
    "   2. extrapolating uncertainties outside the range of the actual data should be viewed with caution.\n",
    "   3. estimates of uncertainties should be viewed with caution when the degrees of freedom in a fit is very low."
   ]
  }
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